Research Article
Research on Intelligent Scheduling Optimization of Non-Full-Load Logistics Vehicle Based on the Monitor Image
@INPROCEEDINGS{10.1007/978-3-030-51103-6_14, author={Rui Li and Haiying Chen}, title={Research on Intelligent Scheduling Optimization of Non-Full-Load Logistics Vehicle Based on the Monitor Image}, proceedings={Multimedia Technology and Enhanced Learning. Second EAI International Conference, ICMTEL 2020, Leicester, UK, April 10-11, 2020, Proceedings, Part II}, proceedings_a={ICMTEL PART 2}, year={2020}, month={7}, keywords={Integration of collection and delivery Vehicle scheduling Dynamic scheduling Time window}, doi={10.1007/978-3-030-51103-6_14} }- Rui Li
Haiying Chen
Year: 2020
Research on Intelligent Scheduling Optimization of Non-Full-Load Logistics Vehicle Based on the Monitor Image
ICMTEL PART 2
Springer
DOI: 10.1007/978-3-030-51103-6_14
Abstract
The traditional logistics vehicle scheduling method only estimates the total scheduling of batch vehicles, without considering the capacity limit of single logistics vehicle. It causes the problem of waste in vehicle transportation. Therefore, a vehicle scheduling method based on monitoring image under time constraints is proposed, using the time displayed in the monitoring image to constrain, the dynamic scheduling model is established by setting up the time window scheduling model to schedule the vehicle tasks within the time window conditions. According to the images obtained from the monitoring, combined with the need to divide several stages under the time constraints, the vehicles to ensure the logistics transportation can be scheduled according to the actual situation, make a highly optimal decision, achieve the maximum vehicle load rate, and ensure the smooth implementation of the dynamic strategy of the non full load logistics vehicle scheduling under the time constraints. Finally, the simulation test results show that the proposed method can improve the efficiency and rationality of logistics vehicle scheduling, the algorithm is stable and reliable, and has strong practicability.
